This study focuses on applicability of Intel Xeon Phi coprocessor for some of the Basic Linear Algebra Subprograms (BLAS) subroutines. Based on Many Integrated Core (MIC) architecture, the vector processing unit (VPU) in Xeon Phi coprocessor provides data parallelism at a very fine grain, working

Abstract—Intel’s Xeon Phi is the first commercial manycore/multi-thread x86-based processor. Xeon Phi belongs to a new breed of high performance computing processors that seek high compute density as well as energy efficiency. However, no highlevel energy model is available for Xeon Phi software

performance characterization analysis of the parallel implementation of the POBPAS for three data sets on two Intel Xeon SMPs. Experimental results indicate that there are no obvious parallel limiting factors in the implementation except memory bandwidth. As a result, it can achieve 11.3X speedup for a larger

and calculating the product of the inverted Cholesky factor with its transpose to get the final inverted matrix. Using high performance data layout, which represents the matrix in the system memory with an optimized cache-aware format, the computation of the three stages is decomposed into fine

considered in performance predictions. Most existing approaches use established prediction models [3, 18] to estimate the performance of already existing complex software systems. Their main focus lies on the questions: i) ”How can we automatically derive or extract the models we need? ” and ii

Abstract Message-oriented event-driven systems are becoming increasingly ubiquitous in many industry do-mains including telecommunications, transportation and supply chain management. Applications in these areas typically have stringent requirements for performance and scalability. To guarantee

present a characterization of the problem space of self-adaptation for service-oriented systems, thus providing a frame of reference where our and other approaches can be classified. Then, we present MOSES, a methodology and a software tool implementing it to support QoS-driven adaptation of a service

workload characterization of SPECjms2007 with the goal to help users understand the internal components of the workload and the way they are scaled, ii) we show how the workload can be customized to exercise and evaluate selected aspects of MOM performance, iii) we present a case study of a leading JMS

In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree

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